Welcome to the third day of Evercore ISI's healthcare conference. With me in attendance is Ramses Erdtman, Chief Operating Officer of Biomea Fusion. Ramses, welcome. Thank you so much for coming down to Miami to spend some time with us. But before we delve into Q&A, I would love to kind of hear your highlights of 2024 and what we could look forward to possibly in 2025. Okay, that's an open question. Thank you. So thank you for inviting us. I really enjoy the depth of the Evercore team. Thank you. Seriously. And we've always had great experiences with them, even at the pharmaceutical stage. So the company Biomea Fusion was founded in 2017. We started actually as an oncology company. We found a pathway that others had, you know, interrogated. And we found that if you inhibit menin directly, covalently binding to menin selectively, you can achieve effects in diabetes that we think are quite unusual, because what they lead to is a proliferation of beta cells. And we have done first the animal experiments in rats, then we went to human cells, and now we're in the clinic. And we're reading out a study of 200 patients. And if you think of the diabetes landscape, you see that there are patients who are really like ourselves here in the room. They're slender. They have a BMI of maybe 20 to 25. Then there are patients who have a BMI of 40. So the pool is quite heterogeneous. We had to learn that a patient who is having maybe insulin resistance as its core defect is behaving differently than one who has insulin insufficiency. So as we're going into this field now, and that's the data we just published two weeks ago, we're seeing that if you proliferate beta cells, which is a very natural mechanism that the female body does during pregnancy, the woman actually does exactly what we're doing. She downregulates menin through prolactin, and then with the downregulation of menin, beta cells start to proliferate. We learned this early on, and we said, this is fascinating. If I could do this safely with a drug, that would be phenomenal for diabetes patients. However, in this pool of patients, who is the one who needs it? We just learned that those that are beta cell deficient or that are insulin deficient have the most benefit, even though we also saw a benefit with those that were resistant to insulin. If you look at it, you think, okay, so there is somebody who's, and you can see in obesity that the body actually tries to overcome the resistance and make more beta cells. I give this patient more beta cells. I do have an impact, but the impact is greater for those where the body is actually completely deficient of the capacity. We're making great strides. We're learning a lot, but this readout that's coming up, and we promised it before the end of the year. That's why at this conference it's just only me here, because everybody else is focused on getting the readout done. This readout is quite important because it shows in a large patient set in three cohorts. We will find out who's the target patient, who's the best responder, and we will also find out what dosing should I use. Should I use four, eight, 12 weeks? Should I use 100 or 200? So we will walk through it, and we will try to give you a good understanding and ourselves who is the target patient that I can easily take forward. We believe beta cell deficiency, and it's not our belief. If you go into the literature, you'll see the decline of beta cells is a hallmark of diabetes, meaning the mass and the function is decreasing over time. So if I grab this patient over here and I give him more beta cells, yes, they do have a benefit, but where can I project that benefit clearly into a Phase 3 study? And that's what we think this readout will give us. Got it. Got it. Thanks. That's very helpful, Ramses. Just want to address the clinical hold that came and went. I mean, you guys actually emerged from that pretty quickly in three and a half months. But I think just from reviewing prior transcripts, you mentioned that despite the clinical hold, there were about 10% of patients who had not completed dosing in the 111 expansion phase. So I guess my question is, what's being done with those patients? And if those patients are censored, will the trial kind of still have enough power to detect what's meaning to detect? Yeah, actually, we never gave guidance on statistical powering for this study. It's three arms. It's 72 patients each arm. There's a lot going on. And the study was disrupted, as you know. However, if you look at what happened with the FDA, I just want to spend one minute just explaining it. The FDA sees a new pathway in a very large disease setting, and they say, what are you guys doing over there? And then Syndax files with their menin inhibitor and a huge safety burden right around the same time. And then they see, oh, there's some LFT elevations, meaning the liver is absorbing from our MOA perspective. There is this glucose that we're downregulating. Where is it going? And if it can't be absorbed as energy, it goes into the liver. So then you get these liver spikes, but for the most part, they're transient. But there's no AE or SAE associated with this. The patient is not vomiting, so you're continuing the study, and the FDA sees it and the fact that they halted us. I actually, I personally, maybe the company has a different viewpoint. I personally found that not to be that sort of. It's PR-wise, obviously not helpful because people need to understand the circumstances. But I actually, for us, digging into these patients was a good exercise. We went through every patient narrative. We gave them every information and that's why it got lifted so fast, because when they saw what we did in the expansion, these elevations didn't occur, these grade three elevations and when they saw that when you start at 100 milligrams and then you dose to 200, you actually do not have an unusual increase in these liver values. And we were lucky that we had designed the Phase 2 with a large patient pool of over 200 patients in a way that you were avoiding that. But that was fortuitous for us. So when the FDA saw the fact that we're monitoring, that you don't see it in the large patient set, and they only occurred at the 200 and 400 milligram dose, they were comfortable with the way we conducted the study. And for us, it's now sort of, okay, we have a partner. The FDA was supportive, meaning they're not there to scold you only. They're actually to help you. And so for me, it was a good exercise. Yes, we should have probably overcommunicated early on so they see we're not Syndax or something different. But it was okay. I mean, we came out really fast, and it didn't stop us much. What it did to the pool of data is we finished a larger sample set of patients, and they were in dosing, but we finished 200 of the intended 216. It's pretty good. Pretty good. Yeah. That's very helpful. I mean, so at this point, Ramses, is there still a potential to go up to 400, or is that completely off the table at this point? 400, we actually didn't see a big improvement. So the capacity to proliferate didn't actually support a 400 dosing. So 200, we think, is roughly where we hit the ceiling for the benefit. And we think with 100 or 200, we will sort of, we will benchmark where we will move forward with those two dose levels. I see. I see. So now I guess you're still anticipating Phase 2 to be top line, week 26 data sometime before the end of the year. Yeah. I think you touched upon this before, but just to kind of drill down on it, just maybe talk about the rationale for patient selection for this expansion phase. Why like 75% of patients will be quote unquote earlier stage, meaning metformin or diet and exercise alone and within seven years since diagnosis? Yeah. So, let's just lean back a year and a half ago when you started this study. This is a new pathway. We have no reference point, and we want to understand what do we do for this very large patient pool and who's responding, right? You look. We enrolled BMI 25 to 40. That's a big risk, but we were not looking at it from a risk perspective. We're looking at it from an exploratory perspective. What can we see in these patients? You have patients zero to seven years. You have patients that are front line, and if you think of oncology studies, if you compare a front line with a relapse patient, that's a very different patient, right? Particularly fourth, fifth, sixth line, and in diabetes, it's similar, but we don't know what this drug does in each of these settings. So we said, okay, likely frontline would be a good way to start. You've had metformin. You have failed metformin. Your A1C goes above the normal range, for sure, of 5.7-7. You're above that range now. You're going up to 8 and 9. And what is that next therapy? That next therapy typically is an SGLT2 inhibitor. They do between 0.5 and 0.9 in A1C reduction. Then they hold, and then they come back. And this, if I could be a second-line agent, right, after metformin or as a strategy, if I could fit into that pool, that would be a good place. So that's why 75% of these patients are of that character. But I also want to know what can I do for a GLP-1 failure? What can I do for patients who are on third- and fourth-line? We said, okay, let's split it up 75 to 25. Got it. That makes sense. Makes sense. And just to clarify too, I guess these early patients presumably have a bigger or larger beta cell pool. Just where, I mean, right now is icovamenib, I can't even pronounce it, icovamenib, more efficacious in this earlier stage population, or is it too early to tell right now? Yeah. Icovamenib. I had longer to practice that. And I tell you, it's not easy to get these names, right? I mean, to get a name approved is a big deal because it has to fit all the languages, et cetera, et cetera. Anyway, so we're now at icovamenib. If you call it 219 right now, it's still okay. So we actually, we haven't fully finished that experiment, right? The only experiment we've done, which we have published, is look at the difference between the subgroups, these subgroups, just to spend one minute on them. And by the way, if you go to the literature page, you see a lot of literature on our website with regards to subgroup analysis. It's fascinating how you can get to precision medicine even in diabetes. And diabetes as a problem is every third or fourth healthcare dollar. So the fact that we need to be more precision oriented makes total sense to me. And so subgroups are a way to identify the treatment. And when you look at the data that we published in subgroups, we actually, which is not our, these ideas of subgroups came through academia, and they use five criteria. They say age at diagnosis, when did you get diabetes for the first time? Your BMI makes sense. Your HbA1c, meaning how toxic is your blood at the moment of coming into a center. And then they look at HOMA-IR, which is a calculation of insulin resistance. How is your body responding to the insulin that you produce? And then HOMA-beta, which is a measure of the productivity of your beta cells. How much are they producing? So with these five criteria, and there is not, age is not one of them, age at diagnosis, but prior lines of therapies are not one of them. So what we've done is, to answer your question, we've done the subgroup analysis that academia has accepted. And there are four groups. And if you look at the four groups, half of them, which is about roughly 55% of the U.S. population or the Western population, fits more into the insulin-deficient two groups there. And then the other half fits more into the insulin-resistant. And we categorized it by those standards. And the readout that we will show you coming up is based on those standards, not on ours. This is accepted. So now, going into the future, I think more and more therapies. You can go to Japan. They're already working on taking a patient and giving, okay, BMI above X, you get this treatment. BMI below, you get that treatment. We will do roughly the same. I think 90% of the resistance or the deficiency separation occurs with BMI. Yeah. It's going to be very easy for us. We will do the same thing. We'll cut BMI as well. We'll look at BMI. If I could use BMI as a factor of decision making, it's very easy to take it into practice. If you are the doctor and you say this drug is good for BMI below 30, done. Got it. Got it. Now, and that's very helpful. Just thinking about the durability response, I think early this year at medical conference, you presented some nice durability data in terms of glycemic response, HOMA-B, C-peptide, just from the escalation phase of the trial. I'm just curious, what may be the reasons for non-response that you saw in a small subset of these patients? So let me think what data you're referring to. So yes, okay. So what can happen is when you look at these patients and what we're doing is we're regrowing this pool, and then we stop therapy. And then we say, okay, what happens three months after, six months after, a year after? And what should happen is that these beta cells that you have regrown are now coming online and they're producing the effect of insulin, which then reduces your blood sugar. So if you measure A1C, it should continue to come down. Makes sense. So now we're saying, okay, who is in this bag of response, right? Who is a responder, who's not a responder? When you look at it, a non-responder could be someone who didn't potentially get enough duration on drug. So we did only four weeks. And then we tested 22 weeks later. There's not one drug in diabetes is given for a moment in time, meaning nobody does that. They all have chronic dosing. So what we did is we tested, is this pool already filled up enough? And then we waited and we said, yeah, for some patients, and it's about a third, we have done enough with four weeks, which is fascinating. Right. That makes sense. Right? And now with others, they may need longer dosing. They may need a higher dose concentration, or they may not respond as well. And those are the ones we think, and that's the data that we just published, the ones that have more of a resistance characteristic, even though when they have received a GLP-1, their resistance could come down and they would benefit as well. Makes total sense. Makes total sense. Just to address the question of drug exposure with food, I mean, I know it's now standard protocol to dose icovamenib two hours after a meal, but some of the dose escalation data shows that food reduces drug exposure, particularly in the 100 milligram group, whereas in the 200 milligram group, food improved exposure. So how do you reconcile these differences? Yeah, that's early on, and the mistake we made is we let you in on the uncertainties of development. You have to do PK studies. You have to understand how this drug works, and if you have a small N, these differences can occur, so we figured all that out in the meantime, and we figured out, hey, if you're within, you know, if you're after food and you're around two hours after food, your pH in your body is adequate to absorb the drug. And sometimes people come in and they haven't eaten in the morning, and you have a different type of absorption. If the drug can't be absorbed and doesn't have a PK effect in your system, how could it have an effect on your disease, right? So you do these studies, obviously, and this is early data that you saw that we published it, but it just shows small N where we're still tinkering and now we're knowing. And so all those 200+ patients are dosed very accurately. And we check it and we protocol it that physician knows, patient knows, hey, please don't vary this because I need the exposure in your blood to understand if the drug is working. Got it. No, that's very interesting. In the interest of time, I just kind of want to pivot to COVALENT-112 in Type 1 diabetes. Just I guess remind us what we could expect in this data set coming out later this month. Is it still open label data for 20 patients? Yeah. So that is, it's unfortunate. So here, when that was the only sort of downside of the hold is, shit, we couldn't finish the dosing of those. We were just, we have the right centers, the right physician. There was so much interest in this pathway from type one patients particularly, and they're so consistent in their behavior and so supportive. So we had targeted 40 patients at 12 weeks. We have finished at the time of the hold, 20 patients at eight weeks. So we're not kind of there. It's going to be a little bit of an incomplete picture when we read it out. And we have to continue enrolling more patients just to understand what are we doing in type one? And is there an autoimmune response that we have to address with potentially another agent, or is icovamenib sufficient? And that's a big ask. There's not one drug that actually does that in a Stage 3 patient, which means a patient who has bona fide Type 1. There is not any drug other than insulin. So trying to go at it where, and maybe just one argument for this, we have found 50 years, patients that had Type 1 diabetes for 50 years are still showing an insulin response when you do a mixed meal tolerance test, which basically means I give you a standard meal. I test your insulin response based on that stringent sort of setup. And if you still have an insulin response, that means you have beta cells. Why have they not been attacked? Good question. And that's what, when we work together with the Joslin Center that is very focused on beta cells, they say, you do have a chance to regenerate those beta cells that have just shown that insulin response. And so that's what we're trying to do. We're trying to regenerate or populate those cells. And if they give us more of an insulin response, that would be very, very beneficial for patients. And if we could see that and we could avoid an autoimmune attack for these cells, wonderful. If not, we just add an autoimmune agent and we will then adjust the study accordingly. Got it. Last question for me, because unfortunately we're almost at time. Just any high level or key nuggets of information regarding your BMF-650, your GLP-1 agonist? Okay, okay. Very good question. We just came out with that. The transcript is phenomenal that you see from the October 30th call. We had actually a conference call based on it because we wanted to give all the data. When you, the GLP-1 expression, right, your receptors are being also controlled by menin. So if you take out menin, you have more GLP-1 receptor expression. If you have more expression, a GLP-1, any GLP-1 has more insulin secretion. That's what we found. So we showed that as one data package. So icovamenib could become a backbone to a GLP-1 therapy and increase persistence. The crux of GLP-1s is they cannot keep patients on drug because they're too toxic. So if we can lower the dose because we increase the receptor expression, if we could do that, wonderful, because then you can be longer on a GLP-1. That would mean longer on this very beneficial drug class. We also came out because the drug class has one aspect. It's mostly injectables. The orals can't compete quite with the benefits. So we said, okay, can we design a drug that is better, that is as good as an injectable, doesn't have the side effect profile? What could that look like? Higher bioavailability, higher protein binding, less PK variability. If we could come up with a drug like that, and that was the goal, we just announced 650 is our compound and we're going to be in patients hopefully by the end of 2025, sometime in 2025, that's what we predicted. We're doing the IND enabling studies and 650 is a monotherapy as a GLP-1, but icovamenib improves GLP-1. That's the other important data point. Excellent. Ramses, I feel like I could talk to you for another half hour. That would be fun. But unfortunately, we're out of time. But thank you so much for making time for us. Thank you for your interest. Extremely interesting conversation and we wish you the best of luck. Thank you. Okay.